Texture classification using hierarchical discriminant analysis
Texture classification using hierarchical discriminant analysis
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DOI：
10.1109/icsmc.2004.1401405
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发表时间：
2004-10
期刊：
影响因子：
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通讯作者：
Syuichi Yasuoka;Yousun Kang;Ken'ichi Morooka;H. Nagahashi
中科院分区：
文献类型：
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作者：
Syuichi Yasuoka;Yousun Kang;Ken'ichi Morooka;H. Nagahashi
Fisher方法作为线性判别分析的代表，在实际中应用最为广泛，在两类分类中非常有效。然而，当它扩展到多类分类问题时，其判别精度可能会变差。其主要原因之一是在Fisher判别准则下建立的判别空间上出现了重叠分布。为了考虑到类之间的重叠，我们的方法建立了一个新的判别空间与层次树结构的重叠类。在本文中，我们提出了一种新的分层判别分析纹理分类。我们可以通过递归地对重叠类进行分组来将判别空间划分为子空间。在实验中，我们对多类纹理图像进行了分类，并与传统方法进行了比较，取得了良好的效果。
As the representative of the linear discriminant analysis, the Fisher method is most widely used in practice and it is very effective in two-class classification. However, when it is expanded to multi-class classification problem, the precision of its discrimination may become worse. One of the main reasons is an occurrence of overlapped distributions on a discriminant space built by Fisher criterion. In order to take such overlap among classes into consideration, our approach builds a new discriminant space with hierarchical tree structure for overlapped classes. In this paper, we propose a new hierarchical discriminant analysis for texture classification. We can divide a discriminant space into subspace by recursively grouping overlapped classes. In the experiment, texture images of many classes are classified based on the proposed method, and we show the outstanding result compared with the conventional method.